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Python What’s python used for?
- Thread starter Malcolm
- Start date
So pretty much anything can be made using Python?
James
Active Coder
Well in a sense yes. There is even a game development engine called godot that uses python
Ash
Bronze Coder
Flask can also be used for websites as that is what I used to create Hive Gamurs. For me, Flask was slightly easier and better to use than Django.
D
Dan-Kode
Guest
Python can be used for a lot of things, depending on your Career Path.
It's mainly used for things like Artificial-Intelligence, Machine-Learning and Data-Science. Now while you can do those sort of stuff with other Languages(E.g. C, Java), Python is probably best for them. Python also has a wide-range of APIs for you to work with. Some notable ones include:
Python can also be used to develop Websites with. The popular Site, Reddit, was originally written in Lisp but at the end of 2005, got re-written in Python. Imagine having to write a Site as big as Reddit, in Python. Not only was that a big re-write to undertake but it also shows how Python can be used for Websites.
Python also has APIs for things like Video Games, GUIs and Data-Science. Pick what APIs you think would be suitable for your Python Project. I'd suggest that you go with the more recognisable ones such as NumPy. Now while you don't need to write everything in Python using an API, your Code will be limited and it will be a lot harder without an API.
It's mainly used for things like Artificial-Intelligence, Machine-Learning and Data-Science. Now while you can do those sort of stuff with other Languages(E.g. C, Java), Python is probably best for them. Python also has a wide-range of APIs for you to work with. Some notable ones include:
- NumPy
- Flask
- Django
Python can also be used to develop Websites with. The popular Site, Reddit, was originally written in Lisp but at the end of 2005, got re-written in Python. Imagine having to write a Site as big as Reddit, in Python. Not only was that a big re-write to undertake but it also shows how Python can be used for Websites.
Python also has APIs for things like Video Games, GUIs and Data-Science. Pick what APIs you think would be suitable for your Python Project. I'd suggest that you go with the more recognisable ones such as NumPy. Now while you don't need to write everything in Python using an API, your Code will be limited and it will be a lot harder without an API.
Ghost
Platinum Coder
Everything has already been said, but I want to add an example of Python use.
My cousin works for a bank and they're using Python to rewrite their entire investment risk management system. With some machine learning and more defined metrics, Python will analyze their finances, global news and laws, etc to help their executives and asset managers make educated decisions, buy or sell various stocks, etc.
It's a simple language compared to others and has a lot of use cases. You can create software, servers for games or online software, scripts, or even malicious code for keyloggers & malware.
My cousin works for a bank and they're using Python to rewrite their entire investment risk management system. With some machine learning and more defined metrics, Python will analyze their finances, global news and laws, etc to help their executives and asset managers make educated decisions, buy or sell various stocks, etc.
It's a simple language compared to others and has a lot of use cases. You can create software, servers for games or online software, scripts, or even malicious code for keyloggers & malware.
NAAZANIQUA
Active Coder
Python is a general-purpose programming language. Therefore, you can use programming languages to develop desktop and web applications. You can also use Python to develop complex scientific and numerical applications. Python is designed with features to facilitate data analysis and visualization.
Very interesting! But it makes you wonder why there are so many other languages, why can't Python do everything?
D
Dan-Kode
Guest
Because Python isn't optimized for everything. Same applies to all Programming-Languages.
Python isn't good for Video Games but C/C++/C# are great for Video Games. C isn't great for AI but Python specializes in AI.
What I'm saying is Python isn't great for everything. Each Language is tailored to different Jobs and Programs. Same is for Python. It's tailored for AI and Data-Science.
mobiosolutions
New Coder
The Python program is highly secure, just like other web application development languages, such as PHP, HTML, and more. Using this, you can hire the code from accessing. Even if you are dealing with sensitive information and products, you can trust Python to keep your web application secure. From simple web frameworks to high-end gaming applications, Python can be used for all. Besides, it is also popular in ML development.
Too much.
Like a lot of languages it starts out with a clear cut set of objectives. Meets them, becomes popular and then a whole load of monoglots try to make the language do what every other language does. The language ends up broken, over complicated and barely full fills it's original purpose.
Python hasn't quite got that bad yet, but there are dozens of examples where python code is used completely out of place.
It is also fairly badly understood at what it's limitations are, resulting in a some horrendous performance side effects.
Don't mean to pick, but the comment from before mine highlights the concern. Python is not in anyway secure. Quite the opposite actually. It's highly insecure. The reason is, it's a script language. They cannot be exhaustively tested, because they are dynamically typed and dynamically bound at runtime.
It's claimed to be an Object Orientated language, boosting secure coding. However it is absolutely NOT an OOP language. It's OOP mechanisms are a stretch to even call OOP as it doesn't support even half of the main corner stones of OOP. No encapsulation. Inheritance is just a hack which can be hacked around easily. Methods are dynamically bound and instance members are just map entries. There are annotations out there that try and put in place adminstrative/static checks on methods to try and implement some of the OOP strictness, but then it starts to fall into the category of pushing the language too far.
It's a rapid application development interrupted script language best served for writing admin tasks, automation and small utilities to support the real applications written in one of the big enterprise languages.
It's use in Datascience and ML et. al is rather curious. From experience, "PySpark" is popular, but invariably the scripts these people write are a liability. Almost always they are trained using small files, small pandas and insist on "collect()" 'ing data locally. NONE of these techniques actually work in a proper Datascience environment when you are handed 14 Terrabytes of data! What actually happens is 2 days later, after you have closed your Juniper notebook, your pyspark is STILL running consuming over a terrabyte of RAM and someone like me comes along and kills it for being annoying.
/rant
Like a lot of languages it starts out with a clear cut set of objectives. Meets them, becomes popular and then a whole load of monoglots try to make the language do what every other language does. The language ends up broken, over complicated and barely full fills it's original purpose.
Python hasn't quite got that bad yet, but there are dozens of examples where python code is used completely out of place.
It is also fairly badly understood at what it's limitations are, resulting in a some horrendous performance side effects.
Don't mean to pick, but the comment from before mine highlights the concern. Python is not in anyway secure. Quite the opposite actually. It's highly insecure. The reason is, it's a script language. They cannot be exhaustively tested, because they are dynamically typed and dynamically bound at runtime.
It's claimed to be an Object Orientated language, boosting secure coding. However it is absolutely NOT an OOP language. It's OOP mechanisms are a stretch to even call OOP as it doesn't support even half of the main corner stones of OOP. No encapsulation. Inheritance is just a hack which can be hacked around easily. Methods are dynamically bound and instance members are just map entries. There are annotations out there that try and put in place adminstrative/static checks on methods to try and implement some of the OOP strictness, but then it starts to fall into the category of pushing the language too far.
It's a rapid application development interrupted script language best served for writing admin tasks, automation and small utilities to support the real applications written in one of the big enterprise languages.
It's use in Datascience and ML et. al is rather curious. From experience, "PySpark" is popular, but invariably the scripts these people write are a liability. Almost always they are trained using small files, small pandas and insist on "collect()" 'ing data locally. NONE of these techniques actually work in a proper Datascience environment when you are handed 14 Terrabytes of data! What actually happens is 2 days later, after you have closed your Juniper notebook, your pyspark is STILL running consuming over a terrabyte of RAM and someone like me comes along and kills it for being annoying.
/rant
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